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Set Distribution Networks: a Generative Model for Sets of Images
Images with shared characteristics naturally form sets. For example, in ...
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Least squares binary quantization of neural networks
Quantizing weights and activations of deep neural networks results in si...
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Geometric Capsule Autoencoders for 3D Point Clouds
We propose a method to learn object representations from 3D point clouds...
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Worst Cases Policy Gradients
Recent advances in deep reinforcement learning have demonstrated the cap...
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Democratizing Production-Scale Distributed Deep Learning
The interest and demand for training deep neural networks have been expe...
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One Framework to Register Them All: PointNet Encoding for Point Cloud Alignment
PointNet has recently emerged as a popular representation for unstructur...
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Unsupervised Style and Content Separation by Minimizing Mutual Information for Speech Synthesis
We present a method to generate speech from input text and a style vecto...
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3D Manhattan Room Layout Reconstruction from a Single 360 Image
Recent approaches for predicting layouts from 360 panoramas produce exce...
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MVX-Net: Multimodal VoxelNet for 3D Object Detection
Many recent works on 3D object detection have focused on designing neura...
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Non-Autoregressive Text Generation with Pre-trained Language Models
Non-autoregressive generation (NAG) has recently attracted great attenti...
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Extracurricular Learning: Knowledge Transfer Beyond Empirical Distribution
Knowledge distillation has been used to transfer knowledge learned by a ...
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Nonlinear Conjugate Gradients For Scaling Synchronous Distributed DNN Training
Nonlinear conjugate gradient (NLCG) based optimizers have shown superior...
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Towards Learning Multi-agent Negotiations via Self-Play
Making sophisticated, robust, and safe sequential decisions is at the he...
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Capsules with Inverted Dot-Product Attention Routing
We introduce a new routing algorithm for capsule networks, in which a ch...
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Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces
Word embedding techniques heavily rely on the abundance of training data...
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PCRNet: Point Cloud Registration Network using PointNet Encoding
PointNet has recently emerged as a popular representation for unstructur...
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VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection
Accurate detection of objects in 3D point clouds is a central problem in...
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Learning from Simulated and Unsupervised Images through Adversarial Training
With recent progress in graphics, it has become more tractable to train ...
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Neural Belief Tracker: Data-Driven Dialogue State Tracking
One of the core components of modern spoken dialogue systems is the beli...
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Actionable Email Intent Modeling with Reparametrized RNNs
Emails in the workplace are often intentional calls to action for its re...
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Morph-fitting: Fine-Tuning Word Vector Spaces with Simple Language-Specific Rules
Morphologically rich languages accentuate two properties of distribution...
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Counter-fitting Word Vectors to Linguistic Constraints
In this work, we present a novel counter-fitting method which injects an...
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Global Pose Estimation with an Attention-based Recurrent Network
The ability for an agent to localize itself within an environment is cru...
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Divide, Denoise, and Defend against Adversarial Attacks
Deep neural networks, although shown to be a successful class of machine...
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Structured Control Nets for Deep Reinforcement Learning
In recent years, Deep Reinforcement Learning has made impressive advance...
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Adversarial Training for Community Question Answer Selection Based on Multi-scale Matching
Community-based question answering (CQA) websites represent an important...
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Learning Sharing Behaviors with Arbitrary Numbers of Agents
We propose a method for modeling and learning turn-taking behaviors for ...
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Mirroring to Build Trust in Digital Assistants
We describe experiments towards building a conversational digital assist...
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Differentiable Approximation Bridges For Training Networks Containing Non-Differentiable Functions
Modern neural network training relies on piece-wise (sub-)differentiable...
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Speaker-Independent Speech-Driven Visual Speech Synthesis using Domain-Adapted Acoustic Models
Speech-driven visual speech synthesis involves mapping features extracte...
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On Modeling ASR Word Confidence
We present a new method for computing ASR word confidences that effectiv...
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Density estimation in representation space to predict model uncertainty
Deep learning models frequently make incorrect predictions with high con...
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Connecting and Comparing Language Model Interpolation Techniques
In this work, we uncover a theoretical connection between two language m...
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Single Training Dimension Selection for Word Embedding with PCA
In this paper, we present a fast and reliable method based on PCA to sel...
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Jointly Learning to Align and Translate with Transformer Models
The state of the art in machine translation (MT) is governed by neural a...
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Neural Network-Based Modeling of Phonetic Durations
A deep neural network (DNN)-based model has been developed to predict no...
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Reverse Transfer Learning: Can Word Embeddings Trained for Different NLP Tasks Improve Neural Language Models?
Natural language processing (NLP) tasks tend to suffer from a paucity of...
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Modeling patterns of smartphone usage and their relationship to cognitive health
The ubiquity of smartphone usage in many people's lives make it a rich s...
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An Exploration of Data Augmentation and Sampling Techniques for Domain-Agnostic Question Answering
To produce a domain-agnostic question answering model for the Machine Re...
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Stochastic Weight Averaging in Parallel: Large-Batch Training that Generalizes Well
We propose Stochastic Weight Averaging in Parallel (SWAP), an algorithm ...
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Voice trigger detection from LVCSR hypothesis lattices using bidirectional lattice recurrent neural networks
We propose a method to reduce false voice triggers of a speech-enabled p...
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Speech Translation and the End-to-End Promise: Taking Stock of Where We Are
Over its three decade history, speech translation has experienced severa...
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Question Rewriting for Conversational Question Answering
Conversational question answering (QA) requires answers conditioned on t...
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Self-supervised Learning of Visual Speech Features with Audiovisual Speech Enhancement
We present an introspection of an audiovisual speech enhancement model. ...
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Learning to Rank Intents in Voice Assistants
Voice Assistants aim to fulfill user requests by choosing the best inten...
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Finding Experts in Transformer Models
In this work we study the presence of expert units in pre-trained Transf...
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Variational Neural Machine Translation with Normalizing Flows
Variational Neural Machine Translation (VNMT) is an attractive framework...
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Modality Dropout for Improved Performance-driven Talking Faces
We describe our novel deep learning approach for driving animated faces ...
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Collegial Ensembles
Modern neural network performance typically improves as model size incre...
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On the generalization of learning-based 3D reconstruction
State-of-the-art learning-based monocular 3D reconstruction methods lear...
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